Software estimating: a description and analysis of current methodologies with recommendations on appropriate techniques for estimating RIT research corporation software projects

This thesis investigated, described, and analyzed six current software estimation methodologies. Included were Boehm\u27s COCOMO, Esterling\u27s Work Productivity Model, Putnam\u27s Life Cycle Model and Albrecht\u27s Function Point Determination. An implementation strategy for software estimation within RIT Research Corporation, a consulting firm, has been developed, based on this analysis. This strategy attempts to satisfy key needs and problems encountered by RIT Research estimators, while providing cost effective, accurate estimates

Towards a model for software project estimating

The use and development of software is an integral and critical part of modern industrial society. The outcomes of many software development and maintenance projects have been less than satisfactory with significant numbers being over schedule, lacking in functionality and over budget. These problems are the result of poor management of both the process and the product. One of the major problems to overcome in the management of software development projects is the ability to predict the outcomes early in the project when there are a large number of unknowns. The ability to reliably predict the outcomes in a repeatable manner requires accurate estimating techniques that are theoretically sound, practical to use, relevant to the current situation and can cope with all the project variables. Whilst a number of estimating techniques have been developed they are poor in their predictive abilities, do not to take a total project approach and are not used by practitioners. This proposal is to define a model that will build on the strengths of the current estimating techniques, account for their weaknesses and provide a framework for the development of practical techniques that encompass all aspects of a software development project

Design & Analysis of Cost Estimation for New Mobile-COCOMO Tool for Mobile Application

Software cost estimation is a resource forecasting method, which is required by the software development process. However, estimating the workload, schedule and cost of a software project is a complex task because it involves predicting the future using historical project data and extrapolating to see future values. For cost estimates for software projects, several methods are used. Among the various software cost estimation methods available, the most commonly used technology is the COCOMO method. Similarly, to calculate software costs, there are several cost estimating tools available for software developers to use. But these released cost estimation tools can only provide parameters (i.e. cost, development time, average personnel) for large software with multiple lines of code. However, if a software developer wants to estimate the cost of a small project that is usually a mobile application, the available tools will not give the right results. Therefore, to calculate the cost of the mobile application, the available cost estimation method COCOMO II is improved to a new model called New Mobile COCOMO Tool. The New Mobile COCOMO tool developed specifically for mobile applications is a boon for software developers working in small software applications because it only includes important multipliers that play a vital role in estimating the cost of developing mobile applications. Therefore, the objective of this paper is to propose a cost estimation model with a special case of COCOMO II, especially for mobile applications, which calculates the person-month, the programmed time and the average personnel involved in the development of any mobile app

Cocomo II as productivity measurement: a case study at KBC.

Software productivity is generally measured as the ratio of size over effort, whereby several techniques exist to measure the size. In this paper, we propose the innovative approach to use an estimation model as productivity measurement. This approach is applied in a case-study at the ICT-department of a bank and insurance company. The estimation model, in this case Cocomo II, is used as the norm to judge about productivity of application development projects. This research report describes on the one hand the set-up process of the measurement environment and on the other hand the measurement results. To gain insight in the measurement data, we developed a report which makes it possible to identify productivity improvement areas in the development process of the case-study company.

A Simple Neural Network Approach to Software Cost Estimation

The effort invested in a software project is one of the most challenging task and most analyzed variables in recent years in the process of project management Software cost estimation predicts the amount of effort and development time required to build a software system It is one of the most critical tasks and it helps the software industries to effectively manage their software development process There are a number of cost estimation models Each of these models have their own pros and cons in estimating the development cost and effort This paper investigates the use of Back-Propagation neural networks for software cost estimation The model is designed in such a manner that accommodates the widely used COCOMO model and improves its performance It deals effectively with imprecise and uncertain input and enhances the reliability of software cost estimates The model is tested using three publicly available software development datasets The test results from the trained neural network are compared with that of the COCOMO model From the experimental results it was concluded that using the proposed neural network model the accuracy of cost estimation can be improved and the estimated cost can be very close to the actual cos